Transcript STRUCTURE OF PRESENTATION

CONDITIONAL CASH TRANSFERS,
SCHOOLING AND CHILD LABOR:
MICRO-SIMULATING BOLSA ESCOLA
By
FRANÇOIS BOURGUIGNON,
FRANCISCO H. G. FERREIRA
PHILLIPPE G. LEITE
Presented by Luke Okafor and Elizabeth Rivard
University of Warsaw
November 19, 2007
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OUTLINE
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INTRODUCTION
BOLSA ESCOLA PROGRAMME
METHODOLOGY
APPRAISAL OF THE STUDY
SUGGESTIONS FOR IMPROVEMENT
CRITIQUE BY SCHWARTZMAN
CONCLUSIONS
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November 19, 2007
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INTRODUCTION
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Cash transfers targeted to poor people with conditions
The Brazilian National Bolsa Escola is a kind of
redistributive programme with features of:
-Means-test
-The behavioral conditionality
-Eligibility criteria
Evaluation of the kind of programme could be:
-Ex-post approaches
-Ex-ante methods
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November 19, 2007
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BOLSA ESCOLA PROGRAMME
Bolsa Escola Programme was created by law in
April 2001
 Eligibility for participation in the programme
-Households with monetary income below 90
Reasi (R$) per month
-with children aged 6 to 15
-85 % school attendance
 Goals of the programme:
-Reduction of current levels of poverty and
inequality
-Provision of incentives for reduction of future
poverty
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November 19, 2007
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ASSUMPTIONS OF THE STUDY
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The decision of how the child’s time allocation is
made within the household ignored
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The decision to send the child to school is last to
made
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The issue of various siblings in same household
ignored
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The composition of the household is exogenous
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November 19, 2007
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METHODOLOGY
The occupational choice variable Si will be modeled
using the standard utility-maximizing interpretation of the
multinomial Logit framework,
Si = k iff Sk(Ai, Xi, Hi; Y-i + yik) + vik > Sj(Ai, Xi, Hi; Y-i +
yij) + vij for j ≠k
(1)
 Collapse non-income explanatory variables into a single
vector Zi and linearize
Ui(j) = Sj(Ai, Xi, Hi; Y-i + yij) + vji = Zi.γj + (Y-i + yij)αj + vij
(2)
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METHODOLOGY
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The observed marketing earning of the child denoted by
wi. Assuming the standard Becker-Mincerian human
capital model, writes:
Log wi = Xi .δ + m*Ind(Si=1) + ui
(3)
Xi set of individual characteristics
Ui random error terms
Ind(Si=1) indicator function
Based on (3) the child’s contribution to the household
income yij under the various alternatives j
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November 19, 2007
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METHODOLOGY
Y = Kwi; y = MKwi; y =Dy
i0
i1
i2
io
= DKwi with M = Exp (m)
where it is assumed that yij values the output or potential
market earnings
Wi is decomposed into in the proportions of k,
1-M and 1-D
Replacing (4)in (2) leads to
Ui(j) = Sj(Ai, Xi, Hi; Y-i + yij) + vji = Zi.γj + Y-i αj +
β.wi + vij with: β0 = α0 K, β1= α1 MK; β2= α2
Dk
(5)
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METHODOLOGY
 This is the final model simulated by the authors. If the
coefficients of α, β, γ, wi and Vij, then the child’s
occupational choice type selected by the household I is
 K* = Arg Max [ Ui (j)]
(6)
 Equation (5) is the benchmark case. If the Bolsa Escola
programme entitled all the children going to school a
transfer of T, then, 5 is replaced by
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Ui(j) = Zi.γj + (Y-i + BEij).αj + β.wi + vij with:
βEi0 = 0 and BEi1=BEi2 =T
(7)
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November 19, 2007
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APPRAISAL OF THE STUDY
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The individual effects could be correlated with schooling
choice and the correlation between the composite error
terms could make the OLS to be biased
The validation of the simulated model on survey data
alone may lead to biased results eg sample bias, age
effects etc
Calibrations based on the simulations afterwards may be
biased as well
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November 19, 2007
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APPRAISAL OF THE STUDY CONTD
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The eligibility condition created problem of
additionality: attendance and learning, a different kind
of social exclusion, and length of the programme
Target assistencialist bias
Table 1: Bolsa Escola in Recife and Belo Horizonte
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November 19, 2007
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APPRAISAL OF THE STUDY CONTD
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Influence of unemployment in the family
Influence of gender on the decision making process
The problem associated with undeclared income
The scored-based proxy for permanent may be too far
from average truth
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November 19, 2007
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SUGGESTIONS FOR IMPROVEMENT
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The use of simulation and CGE may give room for
taking care of changing economic conditions in the
long run
The labour supply model: the intra-labour choice
allocations could be incorporated into the study
Validation and calibration of the model should be
based on data from participants and non-participants
in the Bolsa Escola programmme and the Survey
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CONCLUSIONS-ORIGINAL PAPER
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Take the size of the family into account when
determining which families are eligible
Monitor school attendence rather than school
enrollment
The assumption that in poor families, children
(ages 6-13) do not go to school because they have
to work and little money incentive could change
this situation may be too simplistic.
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November 19, 2007
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CONCLUSIONS-ORIGINAL PAPER
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Education focus of the programme (may have
missed target)
Target transfer to the age with the highest risk
(age 14 and above)
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November 19, 2007
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CRITIQUE BY SCHWARTZMAN
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Patterns of attendance not related to the stipend; limited
government monitoring of attendance
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November 19, 2007
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CRITIQUE BY SCHWARTZMAN
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Missing school for work was not widespread
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November 19, 2007
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CRITIQUE BY SCHWARTZMAN
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Having the stipend decreased the chances of a child working for those aged
5-6 and 14-17, but not those aged 7-13
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November 19, 2007
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CRITIQUE BY SCHWARTZMAN
Children receiving the stipend actually worked more
than those who did not; child labor is mostly rural, ages
15-17
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November 19, 2007
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CRITIQUE BY SCHWARTZMAN
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The least poor do not always receive the stipend:
majority of the poor are urban, but programme
focuses on rural poor
 Of the 12.8 million children in families at the
lowest fifth income quintile, 35% live in rural
areas, but receive 40% of the stipends. Among
the rural poor, 39% receive the stipend; among
the urban poor, only 30%
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November 19, 2007
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CONCLUSIONS-SCHWARTZMAN
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Increase stipend with age (14 and older receive more)
Increase overall quality of schools
Better targeting, implementation and monitoring
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November 19, 2007
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